{"total":20,"rows":[{"id":"2402.10099","title":"Any-Shift Prompting for Generalization over Distributions","created":"2024-02-15","cited_by_count":24,"area":null},{"id":"2407.15773","title":"STAMP: Outlier-Aware Test-Time Adaptation with Stable Memory Replay","created":"2024-07-22","cited_by_count":13,"area":null},{"id":"2407.10784","title":"AdapTable: Test-Time Adaptation for Tabular Data via Shift-Aware Uncertainty Calibrator and Label Distribution Handler","created":"2024-07-15","cited_by_count":6,"area":null},{"id":"2407.13322","title":"Fully Test-Time rPPG Estimation via Synthetic Signal-Guided Feature Learning","created":"2024-07-18","cited_by_count":6,"area":null},{"id":"2409.08566","title":"Hybrid-TTA: Continual Test-time Adaptation via Dynamic Domain Shift Detection","created":"2024-09-13","cited_by_count":5,"area":null},{"id":"2410.14178","title":"Feature Augmentation based Test-Time Adaptation","created":"2024-10-18","cited_by_count":4,"area":null},{"id":"2402.04958","title":"Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation","created":"2024-02-07","cited_by_count":3,"area":null},{"id":"2508.13445","title":"ASAP: Unsupervised Post-training with Label Distribution Shift Adaptive Learning Rate","created":"2025-08-19","cited_by_count":3,"area":null},{"id":"2603.01040","title":"Fed-ADE: Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift","created":"2026-03-01","cited_by_count":2,"area":null},{"id":"2311.18270","title":"Beyond Entropy: Style Transfer Guided Single Image Continual Test-Time Adaptation","created":"2023-11-30","cited_by_count":1,"area":null},{"id":"2505.10641","title":"FRET: Feature Redundancy Elimination for Test Time Adaptation","created":"2025-05-15","cited_by_count":1,"area":null},{"id":"2505.16251","title":"Graph-Smoothed Bayesian Black-Box Shift Estimator and Its Information Geometry","created":"2025-05-22","cited_by_count":1,"area":null},{"id":"2602.05937","title":"Multi-Scale Global-Instance Prompt Tuning for Continual Test-time Adaptation in Medical Image Segmentation","created":"2026-02-05","cited_by_count":1,"area":null},{"id":"2607.08164","title":"Continual Test-Time Adaptation in Computer Vision: Methods, Benchmarks, and Future Directions","created":"2026-07-09","cited_by_count":1,"area":null},{"id":"2403.01344","title":"Mitigating the Bias in the Model for Continual Test-Time Adaptation","created":"2024-03-02","cited_by_count":0,"area":null},{"id":"2411.02047","title":"Theory-inspired Label Shift Adaptation via Aligned Distribution Mixture","created":"2024-11-04","cited_by_count":0,"area":null},{"id":"2411.15204","title":"Label Distribution Shift-Aware Prediction Refinement for Test-Time Adaptation","created":"2024-11-20","cited_by_count":0,"area":null},{"id":"2604.17542","title":"Dual Strategies for Test-Time Adaptation","created":"2026-04-19","cited_by_count":0,"area":null},{"id":"2604.20824","title":"Stabilizing In-Context Multi-Source Domain Adaptation for Biomedical Images Through Controls","created":"2026-04-22","cited_by_count":0,"area":null},{"id":"2608.00559","title":"Test-Time Curriculum for Open-Set AIGC Detection","created":"2026-08-01","cited_by_count":0,"area":null}],"next_cursor":null}